Development of grey wolf optimization based modified fast terminal sliding mode controller for three phase interleaved boost converter fed PV system

The conventional MPPT method has drawbacks, such as that under partial shading conditions, several peaks occur and identifying the global peak is difficult. It may converge to a local peak and lead to poor conversion efficiency and tracking efficiency. Implementation of a hybrid algorithm by integrating P&O and metaheuristic algorithms can perform better under partial shading conditions. But the tracking speed is low and the response time is longer. To mitigate the issues mentioned above, a new hybrid algorithm has been suggested that integrates GWO and a modified fast terminal sliding mode controller (MFTSMC). The suggested method with three phase ILBC is incorporated into the PV system. The MATLAB tool is employed to experiment with this study. The performance of GWO-MFTSMC is analysed through MATLAB/ SIMULINK and compared with the performance of ANN-FTSMC and PSO-FTSMC algorithm based MPPT techniques. A hardware prototype is developed and tested for 5 × 200 W solar PV modules with the GWO-MFTSMC algorithm. The proposed method conversion efficiency is 99.72% and 96.15% under simulation and hardware realisation, respectively, which is higher than the ANN-FTSMC and PSO-FTSMC methods.

The Simulink diagram shown in the Fig. 2 has PV modules, three phase interleaved boost converter with GWO-MFTSMC based MPPT algorithm.Since it ILBC is used, the output voltage is always greater than input voltage which is based on the duty ratio.The proposed circuit has MOSFET switches which are turned on with 120° phase difference since it has only three phases.The switching frequency for the proposed system is 20 kHz.The value of inductors and capacitor are 120 μH and 300 μF respectively.For the PV system shown above, load resistance is assumed as 10 ohms.The input voltage is obtained from PV modules and output is fed to the load resistance which is assumed as standalone load.The flowchart of the GWO-MFTSMC algorithm implemented for the charge controller is given in Fig. 3. Table 1 shows the specifications of PV panel chosen which is Bosch Solar Energy c-Si M72NA41126 300 W P .
The suggested MPPT technique involves calculating and updating the fitness value or position of grey wolves.If the grey wolves' position coincides with that of their prey, it can be inferred that the algorithm has reached the global peak.In the proposed GWO-MFTSMC, the presence of modified fast terminal sliding mode controller reduces the oscillations around GMPP and makes the system to settle quickly.If the new power value (P new ) is higher than the old power value (P old ), the pulse width modulation (PWM) duty cycle is raised to maximize the power extraction from the photovoltaic array.If P new is lower than P old , the duty cycle is decreased to restore the system to its prior highest power.
The maximum power point algorithm, when paired with a controller, is characterized by its, ease of implementation, simplicity, low cost, and high level of precision.The MFTSM switching technique entails the adjustment of a collection of unspecified parameters α k , β k , γ k , and λ k , as depicted in Fig. 3.The selection of these operational limits is a challenging and takes more time.Due to the diminishing effectiveness of the iterative trial-and-error processes, the tuning problem is reformulated as a restricted optimization program.

Ethical approval
This paper does not contain any studies with human participants or animals performed by any of the authors. (2) ; f SW is switching frequency and L is Inductor

Results and discussion
The GWO-MFTSMC based MPPT algorithm has been simulated using MATLAB/Simulink.Three phase ILBC has been used as a power converter with 0.5 as duty ratio with voltage conversion rate is 2. To analyse the proposed system performances, two hybrid algorithms PSO-FTSMC and ANN-FTSMC were simulated and compared with proposed system.Six PV panels were used in the PV array.The efficiencies are determined according to the measured power at output and input.The implementation of the GWO-MFTSMC MPPT charge controller significantly enhances the efficiency.In PSO based MPPT, each position is updated regularly which enables to track its position and fitness value in search area to get better solution.In each interaction, particle velocity and position are updated which yields best solution locally and globally.The proposed system performances were tested under three different cases with rapidly changing irradiance.The three test cases were mentioned in the Table 2.These three cases demonstrates the PV system performance under partial shading / rapidly changing weather conditions.
(i) Case I Initially six PV panels were received 600 W/m 2 and later it has been increased to 850 W/m 2 and 950 W/m 2 with constant temperature.From the Fig. 4 it can be observed that more power fluctuations when the irradiance level is at 600 W/m 2 .The peak power which can be obtained from PV array is 1080 W. the power delivered by PV panels through PSO-FTSMC is 998 W, ANN-FTSMC is 1053 W and GWO-FTSMC is 1069 W. The power conversion efficiency is more in GWO-MFTSMC (98.99%) than PSO-FTSMC (92.46%) and ANN-FTSMC(97.48%).Figures 5 and 6 shows that oscillations are less in PV's output voltage and current respectively using GWO-MFTSMC technique.
When the irradiance levels are changed from 600 to 850 W/m 2 , the power generated from PV array has been increased from 998 to 1418 W in PSO-FTSMC technique.Similarly ANN-FTSMC has increased power from 1053 to 1499 W and GWO-MFTSMC has increased from 1069 to 1520 W. The conversion efficiency has also improved in all three techniques in which the proposed technique GWO-MFTSM has conversion efficiency of 99.39%.The output voltage, current and power values at three irradiance levels are shown in the Table 3.
(ii) Case II In this case, irradiance levels were changed from 700 to 900 W/m 2 and 950 W/m 2 .The temperature is maintained constant.The Fig. 7 depicts that oscillations are reduced in GWO-MFTSMC than PSO-FTSMC and ANN-FTSMC technique.The peak power which can be obtained from PV array is 1260 W when irradiance is 700 W/         When the irradiance levels are changed from 700 to 900 W/m 2 , the power generated from PV array has been increased from 1173 to 1512 W in PSO-FTSMC technique.Similarly ANN-FTSMC has increased power from 1221 to 1577 W and GWO-MFTSMC has increased from 1246 to 1607 W. The conversion efficiency has also improved in all three techniques in which the proposed technique GWO-MFTSM has conversion efficiency of 99.24%.The output voltage, current and power values at three irradiance levels are shown in the Table 4.
(iii) Case III Irradiance levels were changed from 750 to 900 W/m 2 and 100 W/m 2 .The temperature is maintained constant.The peak power obtained from PV array is 1350 W when irradiance is 750 W/m 2 , 1620 W when irradiance is 900 W/m 2 and 1800 W when irradiance is 1000 W/m 2 .The power generated from PV array when irradiance at 750 W/m 2 through PSO-FTSMC is 1265 W, ANN-FTSMC is 1316 W and GWO-FTSMC is 1339 W. The power conversion efficiency is more in GWO-MFTSMC (99.18%) than PSO-FTSMC (93.37%) and ANN-FTSMC

Conclusion
The hybrid GWO-MFTSMC technique has been proposed for a PV system with three phase ILBC.A comparison between the GWO-MFTSMC algorithm, PSO-FTSMC and ANN-FTSMC algorithm has been done in simulation and in hardware realization.Both simulation results and hardware reveals that the GWO-MFTSMC algorithm offers superior efficiency and reliability in tracking power from 6 × 300 (simulation) and 5 × 200 W (hardware realization) photovoltaic modules, particularly in situations with rapid fluctuations in irradiance.The    experimental outcomes shown that the proposed system is dominating in terms of efficiency (99.72% and 96.15% in simulation and in hardware realization respectively) compared to the conventional design.The settling time is also very less for proposed method (0.096s in simulation and 0.0352s in hardware realization) than conventional PSO-FTSMC and ANN-FTSMC methods.8).8).

P
max = maximum power 300 Watts V oc = open circuit voltage 46 Volts I sc = short circuit current 8.44 Amps I MPP = operating current 8.0 Amps V MPP = operating voltage 37.5 Volts Temperature constant of V oc − (0.36)%/°C Temperature constant of I sc (0.05)%/°C

Figure 15 .
Figure 15.Comparison of PV's output current for all three MPPTS based on hardware results.

Figure 16 .
Figure 16.Comparison of PV's output power for all three MPPTS based on hardware results.
Capacitance and V o is voltage ripple Figure 1.Block diagram of proposed GWO-MFTSMC.

Table 2 .
Three different cases with changing irradiance level and constant temperature.

Table 3 .
The output power, voltage and current of PV array with different irradiance under Case I.

Table 6 .
Comparison of output power, conversion efficiency and settling time of PSO-FTSMC, ANN-FTSMC and GWO-MFTSMC algorithm.

Table 8 .
Comparison of conversion efficiency and settling time of PSO-FTSMC, ANN-FTSMC and GWO-MFTSMC MPPTs at various irradiance levels.